Authentication of Argentinean extra-virgin olive oils using three-way fluorescence and two-way near-infrared data fused with multi-block DD-SIMCA.

A trending problem of Extra Virgin Olive Oil (EVOO) adulteration is investigated using two analytical platforms, involving: (1) Near Infrared (NIR) spectroscopy, resulting in a two-way data set, and (2) Fluorescence Excitation-Emission Matrix (EEFM) spectroscopy, producing three-way data. The related instruments were employed to study genuine and adulterated samples. Each data set was first separately analyzed using the Data Driven-Soft Independent Modeling of Class Analogies (DD-SIMCA) method, based on Principal Component Analysis (for the two-way NIR data) and PARallel FACtor analysis (for the three-way EEFM data). The data sets were then processed together using the multi-block fusion method, based on the concept of Cumulative Analytical Signal (CAS). A comparison of the data processing methods in terms of sensitivity, specificity and selectivity showed the following order of excellence: NIR < EEFM < NIR + EEFM. This finding confirms the effectiveness of multi-block data fusion, which cumulatively improves the model performance.

Characterization of hAT DNA transposon superfamily in the genome of Neotropical fish Apareiodon sp.

DNA transposons are diverse in fish genomes and have been described to generate genomic evolutionary novelties. hAT transposable element data are scarce in Teleostei genomes, making it challenging to conduct comparative genomic studies to understand their neutrality or function. This study aimed to perform a genomic and molecular characterization of hAT copies to assess the diversity of these elements and associate changes in these sequences to genomic and karyotypic novelties in Apareiodon sp. The data revealed that hAT TEs are highly abundant in the Apareiodon sp. genome, with few possibly autonomous copies. Highly conserved sequences with likely functional transposases were observed in nine hAT elements. A great diversity of hAT subgroups was observed, especially from Ac, Charlie, Blackjack, Tip100, hAT6, and hAT5, and a similar wave of hAT genomic invasion was identified in the genome for these six groups of hAT sequences. The data also revealed a distinct number of microsatellites within degenerated hAT copies. hAT sites were demonstrated to be dispersed in the Apareiodon sp. chromosomes and not involved in W chromosome-specific region differentiation. In conclusion, the genomic analysis revealed a great diversity of hAT elements, possible autonomous copies, and differentiation of degenerated transposable elements into tandem sequences.

Complete blood count as a biomarker for preeclampsia with severe features diagnosis: a machine learning approach.

OBJECTIVE: This study introduces the complete blood count (CBC), a standard prenatal screening test, as a biomarker for diagnosing preeclampsia with severe features (sPE), employing machine learning models. METHODS: We used a boosting machine learning model fed with synthetic data generated through a new methodology called DAS (Data Augmentation and Smoothing). Using data from a Brazilian study including 132 pregnant women, we generated 3,552 synthetic samples for model training. To improve interpretability, we also provided a ridge regression model. RESULTS: Our boosting model obtained an AUROC of 0.90±0.10, sensitivity of 0.95, and specificity of 0.79 to differentiate sPE and non-PE pregnant women, using CBC parameters of neutrophils count, mean corpuscular hemoglobin (MCH), and the aggregate index of systemic inflammation (AISI). In addition, we provided a ridge regression equation using the same three CBC parameters, which is fully interpretable and achieved an AUROC of 0.79±0.10 to differentiate the both groups. Moreover, we also showed that a monocyte count lower than 490 / m m 3 yielded a sensitivity of 0.71 and specificity of 0.72. CONCLUSION: Our study showed that ML-powered CBC could be used as a biomarker for sPE diagnosis support. In addition, we showed that a low monocyte count alone could be an indicator of sPE. SIGNIFICANCE: Although preeclampsia has been extensively studied, no laboratory biomarker with favorable cost-effectiveness has been proposed. Using artificial intelligence, we proposed to use the CBC, a low-cost, fast, and well-spread blood test, as a biomarker for sPE.

Methods for multi-omic data integration in cancer research.

Multi-omics data integration is a term that refers to the process of combining and analyzing data from different omic experimental sources, such as genomics, transcriptomics, methylation assays, and microRNA sequencing, among others. Such data integration approaches have the potential to provide a more comprehensive functional understanding of biological systems and has numerous applications in areas such as disease diagnosis, prognosis and therapy. However, quantitative integration of multi-omic data is a complex task that requires the use of highly specialized methods and approaches. Here, we discuss a number of data integration methods that have been developed with multi-omics data in view, including statistical methods, machine learning approaches, and network-based approaches. We also discuss the challenges and limitations of such methods and provide examples of their applications in the literature. Overall, this review aims to provide an overview of the current state of the field and highlight potential directions for future research.

Evaluation of statistical process control charts for infant mortality monitoring in Brazilian cities with different population sizes.

OBJECTIVES: The control chart is a classic statistical technique in epidemiology for identifying trends, patterns, or alerts. One meaningful use is monitoring and tracking Infant Mortality Rates, which is a priority both domestically and for the World Health Organization, as it reflects the effectiveness of public policies and the progress of nations. This study aims to evaluate the applicability and performance of this technique in Brazilian cities with different population sizes using infant mortality data. RESULTS: In this article, we evaluate the effectiveness of the statistical process control chart in the context of Brazilian cities. We present three categories of city groups, divided based on population size and classified according to the quality of the analyses when subjected to the control method: consistent, interpretable, and inconsistent. In cities with a large population, the data in these contexts show a lower noise level and reliable results. However, in intermediate and small-sized cities, the technique becomes limited in detecting deviations from expected behaviors, resulting in reduced reliability of the generated patterns and alerts.

Gaucher disease in Brazil: a comprehensive 16 year retrospective study on survival, cost, and treatment insights.

Background: Gaucher's disease (GD), a lysosomal storage disorder, poses significant treatment challenges. This 23-year study assesses survival rates and treatment efficacy in Brazilian GD patients, integrating data from a 16-year cohort (2000-2015) and the TABNET/DATASUS medicines distribution data (1999-2022). Objective: To investigate the survival of GD patients in Brazil, identifying key risk factors and evaluating the impact of treatments funded by the Brazilian National Health System (SUS). Methodology: A 16-year retrospective cohort study was conducted using the National Database of SUS. Patients diagnosed with GD and treated with Enzyme Replacement Therapy (ERT) or Substrate Synthesis Inhibition (SSI) from 2000 to 2015 were included. Survival analysis was performed using Kaplan-Meier method and Cox proportional hazards model. The data from TABNET/DATASUS system from 1999 to 2022 was used to assess the trend in drug distribution beyond the main cohort. Results: The study included 1,234 patients. Survival rates at 5 and 10 years were 93.2% and 88.5%, respectively, with age and comorbidities like diabetes, cardiovascular diseases, and Parkinson's disease significantly affecting survival. Patients who received doses lower than DDD (n = 880) demonstrated a survival probability of 91.8%. In contrast, those with doses equal to the DDD (n = 15) showed a 100% survival probability, as no events were observed in this group. The greater than DDD group (n = 339) exhibited a survival probability of 81%. A log-rank test indicated a borderline statistical significance (p = 0.058) in the survival distributions among the different DDD adherence, with the lower dose group showing a favorable trend. Conclusion: This study provides insights into the survival rates and associated risk factors for GD patients in Brazil, contributing to the global understanding of GD and its management. While we acknowledge the inherent limitations of relying largely on electronic medical records and categorical codes, our findings underscore the need for early diagnosis, timely initiation of treatment, effective management of comorbidities, and personalized dosing strategies to improve patient outcomes. Future studies should aim to incorporate clinical verification of electronic data to further enhance the reliability and applicability of these findings.

Draft genome sequence data of Fusarium verticillioides strain REC01, a phytopathogen isolated from a Peruvian maize.

Fusarium verticillioides represents a major phytopathogenic threat to maize crops worldwide. In this study, we present genomic sequence data of a phytopathogen isolated from a maize stem that shows obvious signs of vascular rot. Using rigorous microbiological identification techniques, we correlated the disease symptoms observed in an affected maize region with the presence of the pathogen. Subsequently, the pathogen was cultured in a suitable fungal growth medium and extensive morphological characterization was performed. In addition, a pathogenicity test was carried out in a DCA model with three treatments and seven repetitions. De novo assembly from Illumina Novaseq 6000 sequencing yielded 456 contigs, which together constitute a 42.8 Mb genome assembly with a GC % content of 48.26. Subsequent comparative analyses were performed with other Fusarium genomes available in the NCBI database.

Insulin reference intervals in Brazilian adolescents by direct and indirect approaches: validation of a data mining method from laboratory data

Abstract Objective To determine reference intervals (RI) for fasting blood insulin (FBI) in Brazilian adolescents, 12 to 17 years old, by direct and indirect approaches, and to validate indirectly determined RI. Methods Two databases were used for RI determination. Database 1 (DB1), used to obtain RI through a posteriori direct method, consisted of prospectively selected healthy individuals. Database 2 (DB2) was retrospectively mined from an outpatient laboratory information system (LIS) used for the indirect method (Bhattacharya method). Results From DB1, 29345 individuals were enrolled (57.65 % female) and seven age ranges and sex partitions were statistically determined according to mean FBI values: females: 12 and 13 years-old, 14 years-old, 15 years-old, 16 and 17 years-old; and males: 12, 13 and 14 years-old, 15 years-old, 16 and 17 years-old. From DB2, 5465 adolescents (67.5 % female) were selected and grouped according to DB1 partitions. The mean FBI level was significantly higher in DB2, on all groups. The RI upper limit (URL) determined by Bhattacharya method was slightly lower than the 90 % CI URL directly obtained on DB1, except for group female 12 and 13 years old. High agreement rates for diagnosing elevated FBI in all groups on DB1 validated indirect RI presented. Conclusion The present study demonstrates that Bhattacharya indirect method to determine FBI RI in adolescents can overcome some of the difficulties and challenges of the direct approach.

Correlation between disease severity indices and quality of life measurement tools in atopic dermatitis patients / Correlación entre los índices de gravedad de la enfermedad y las herramientas de medición de la calidad de vida en pacientes con dermatitis atópica

INTRODUCTION: Reports regarding the correlation and effect size of change of the full spectrum of quality of life and disease severity measures applied in-person to patients with atopic dermatitis are scarce. OBJECTIVES: To assess quality-of-life with 3 different instruments and to evaluate disease severity indices and to determine their correlation and effect size of change between two measurements. MATERIALS AND METHODS: Patient-level data were obtained through two in-person visits. Sociodemographic information and data related to disease distribution, severity (through the BSA, EASI, SCORAD, POEM, and itching scales), and the impact of atopic dermatitis on quality of life using the DLQI and Skindex-29, and EQ-5D, were assessed. The correlation between change in quality-of-life scores and disease severity scores in addition to the standardized effect size were also evaluated. RESULTS: Only 139 out of 212 patients completed the follow-up visit. BSA highly correlated with SCORAD and EASI, and the lowest correlation was found with POEM. The best correlation of pruritus VAS was found with sleep disturbance. The SCORAD score highly correlated with EASI, and the lowest correlation was found with POEM. The magnitude of the effect at initiation of the study vs follow-up was in average moderate to important. CONCLUSIONS: Patients with atopic dermatitis experience a substantial burden on quality of life. Disease activity correlates better with quality-of-life measurements when the disease is less severe after starting therapy. POEM and Skindex-29 seem to be optimal to determine disease severity and quality of life in adults with atopic dermatitis.

Introducción: La información publicada sobre la correlación entre la magnitud del efecto de todo el espectro de la calidad de vida y la gravedad de la enfermedad en pacientes con dermatitis atópica es escasa. Objetivos: Evaluar la calidad de vida con tres instrumentos diferentes y los índices de gravedad de la enfermedad en pacientes con dermatitis atópica para determinar su correlación y el tamaño del efecto del cambio. Materiales y métodos: Los datos de los pacientes se obtuvieron a partir de dos visitas. Se evaluó la información sociodemográfica y los datos relacionados con la distribución y la gravedad de la enfermedad (mediante de las escalas BSA, EASI, SCORAD, POEM, prurito) y el impacto de la dermatitis atópica en la calidad de vida utilizando el Dermatology Life Quality Index, Skindex-29 y EQ-5D. También se evaluó la correlación entre el cambio en las puntuaciones de calidad de vida y las de gravedad de la enfermedad, además del tamaño del efecto estandarizado. Resultados: Solo 139 de los 212 pacientes completaron la visita de seguimiento. El área de superficie corporal se correlacionó fuertemente con el SCORAD y el EASI, y la correlación más débil fue con el POEM. La mejor correlación del prurito medido con la escala visual análoga se halló con la alteración del sueño. El puntaje SCORAD se correlacionó altamente con el EASI mientras que la correlación más baja se encontró con el POEM. La magnitud del efecto al inicio del estudio respecto al seguimiento fue en promedio de moderada a importante. Conclusiones: Los pacientes con dermatitis atópica experimentan una carga sustancial en la calidad de vida. La actividad de la enfermedad se correlaciona mejor con las mediciones de calidad de vida cuando esta es menos grave, después de comenzar la terapia. Los índices POEM y Skindex-29 parecen ser óptimos para determinar la gravedad de la enfermedad y la calidad de vida en adultos con dermatitis atópica.

Intersectional equity in Brazil's remote rural municipalities: the road to efficiency and effectiveness in local health systems.

Objective: The Brazilian remote rurality has been classified more reliably only recently, according to demographic density, proportion of urban population, and accessibility to urban centers. It comprises 5.8% of the municipalities, in nearly half of the states, with a population of 3,524,597 (1.85%). Remote rural localities (RRL) have reduced political/economic power, facing greater distances and barriers. Most health strategies are developed with the urban space in mind. We aim to understand how RRL are positioned concerning efficiency/effectiveness in health, compared to other urban-rural typologies of Brazilian localities, focusing on Primary Health Care (PHC), and its organizational models. Methods: We evaluated the efficiency and effectiveness of the organizational models using the health production model, from 2010-2019, gradually deepening the immersion into the RRL reality. We analyzed the human and financial resources dimensions, emphasizing teams, the results of PHC actions, and health levels. We used the fixed effects model and data envelopment analysis, cross-sectioned by intersectional inequities. We compared the Brazilian states with and without RRL, Brazilian municipalities according to rural-urban typologies, and RRL clusters. Results: Brazilian RRL states show superior resource/health efficiency through services utilization according to health needs. The remote rural typology demonstrated greater efficiency and effectiveness in health than the other typologies in the RRL states. The organizational models with the Family Health Strategy (FHS) teams and the Community Health Worker (CHW) visits played a key role, together with local per capita health expenditures and intergovernmental transfers. Thus, financial resources and health professionals are essential to achieve efficient/effective results in health services. Among the RRL, the Amazon region clusters stand out, denoting the importance of riverine and fluvial health teams, the proportion of diagnostic/treatment units in addition to the proportion of illiteracy and adolescent mothers along with the inequity of reaching high levels of schooling between gender/ethnicity. Conclusion: Hopefully, these elements might contribute to gains in efficiency and effectiveness, prioritizing the allocation of financial/human resources, mobile FHS teams, availability of local diagnosis/treatment, and basic sanitation. Finally, one should aim for equity of gender/ethnicity in income and education and, above all, of place, perceived in its entirety.

Enhancing Security of Telemedicine Data: A Multi-Scroll Chaotic System for ECG Signal Encryption and RF Transmission.

Protecting sensitive patient data, such as electrocardiogram (ECG) signals, during RF wireless transmission is essential due to the increasing demand for secure telemedicine communications. This paper presents an innovative chaotic-based encryption system designed to enhance the security and integrity of telemedicine data transmission. The proposed system utilizes a multi-scroll chaotic system for ECG signal encryption based on master-slave synchronization. The ECG signal is encrypted by a master system and securely transmitted to a remote location, where it is decrypted by a slave system using an extended state observer. Synchronization between the master and slave is achieved through the Lyapunov criteria, which ensures system stability. The system also supports Orthogonal Frequency Division Multiplexing (OFDM) and adaptive n-quadrature amplitude modulation (n-QAM) schemes to optimize signal discretization. Experimental validations with a custom transceiver scheme confirmed the system's effectiveness in preventing channel overlap during 2.5 GHz transmissions. Additionally, a commercial RF Power Amplifier (RF-PA) for LTE applications and a development board were integrated to monitor transmission quality. The proposed encryption system ensures robust and efficient RF transmission of ECG data, addressing critical challenges in the wireless communication of sensitive medical information. This approach demonstrates the potential for broader applications in modern telemedicine environments, providing a reliable and efficient solution for the secure transmission of healthcare data.

Predictive models for heat stress assessment in Holstein dairy heifers using infrared thermography and machine learning.

Heat stress is a condition that impairs the animal's productive and reproductive performance, and can be monitored by physiological and environmental variables, including body surface temperature, through infrared thermography. The objective of this work is to develop computational models for classification of heat stress from respiratory rate variable in dairy cattle using infrared thermography. The database used for the construction of the models was obtained from 10 weaned heifers, housed in a climate chamber with temperature control, and submitted to thermal comfort and heat wave treatments. Physiological and environmental data were collected, as well as thermographic images. The machine learning modeling environment used was IBM Watson, IBM's cognitive computing services platform, which has several data processing and mining tools. Classifier models for heat stress were evaluated using the confusion matrix metrics and compared to the traditional method based on Temperature and Humidity Index. The best accuracy obtained for classification of the heat stress level was 86.8%, which is comparable to previous works. The authors conclude that it was possible to develop accurate and practical models for real-time monitoring of dairy cattle heat stress.

Impact of implicit vs. explicit Instructions on tactical performance in under-20 soccer players.

Introduction: This study aimed to verify whether implicit and explicit informational constraints generate differences in tactical performance and behavior in U-20 national-level soccer players. Methods: Thirty-two under-20 male athletes from two clubs participated. Four 4-a-side small-sided games (SSG) protocols were used: R1 - explicit rule for high-press marking, R2 - implicit rule for high-press marking, R3 - game with both previous rules simultaneous and FR - free game, without additional rules. SSGs comprised 4 vs. 4+ goalkeepers games on a 42 m × 29 m field. Position data from 10 Hz Global Positioning System (GPS) devices were used to evaluate individual and collective tactical behavior (spatial occupation metrics) and performance (interpersonal coordination). MANOVA was used for normally distributed variables, and Friedman's with Dunn or Bonferroni post hoc was used for variables without normal distribution. For SEI, an ANOVA was used with Bonferroni post hoc. Results: The R1 protocol showed higher SEI, length, width, and LpWratio than the FR protocol (p = 0.009). There was an effect of the different protocols in SEI values (p < 0.001). Under the explicit rule, players also showed the highest in-phase interpersonal coordination values (p < 0.001). Discussion: Providing players with explicit tactical instructions improves tactical performance acutely for high-pressing defensive actions.

Taylor's law on abundance unravels the role of traits and environmental conditions on population dynamics.

The variance-mean scaling in population abundance or Taylor's power law (TPL) has been reported hundreds of times and is related to ecological processes such as competition, dispersal or territoriality. In this sense, the TPL was extensively validated to resume population variability and to show the action of ecological mechanisms. Baumgartner and Peláez (2024) combine databases of fish dynamics along the United States, species traits, species phylogeny and climatic conditions, estimating the TPL for 180 species along 972 populations. The observed scaling suggests that the variability of the population decreases with abundance. Notably, 68% of the variation in the variance-mean scaling was explained by species traits and environmental conditions. Specifically, the life history of the species, associated with its body size, was the main explanation for the TPL, also reporting that the variability of the population increased faster with mean abundance in the headwaters than in other river sections. Equally important, the diversity of the community in which the species were inserted did not affect the scaling. These results provide overwhelming evidence on the nature of TPL on large geographic scales and how they are affected by species biology and environmental conditions. A contribution that should motivate further empirical and theoretical analysis of the TPL and its determinants.

El escalamiento en varianza con la media de la abundancia poblacional, ha sido reportado en cientos de sistemas y es conocido como Ley Poder de Taylor (TPL, de sus siglas en inglés). Este escalamiento se ha relacionado con la importancia de la competencia, dispersión o territorialidad, resumiendo la dinámica poblacional y su conexión con distintos mecanismos ecológicos. El estudio publicado por Baumgartner y Peláez (2024) combina bases de datos de dinámica de peces en los Estados Unidos de América, de sus rasgos, filogenia y ambientales, estimando la TPL para un total de 180 especies a lo largo de 972 poblaciones. El escalamiento observado sugiere que la variabilidad disminuye con la abundancia de las poblaciones. Notablemente, el 68% de la variación en el escalamiento fue explicado por los rasgos de las especies (historia de vida y tamaño corporal) y las condiciones ambientales. Aumentando más rápidamente la variabilidad en la dinámica poblacional con la abundancia media en las cabeceras que en otras secciones del río. Igualmente importante fue la falta de efectos significativos de la biodiversidad de la comunidad sobre el escalamiento varianza­media de sus poblaciones. Estos resultados proporcionan una contundente evidencia sobre la naturaleza de la TPL en grandes escalas geográficas y cómo se ve afectada por la biología de las especies y las condiciones ambientales. Resultados y abordajes que sugieren futuros análisis empíricos y teóricos sobre la TPL y sus determinantes.

Spatial scales of COVID-19 transmission in Mexico.

During outbreaks of emerging infectious diseases, internationally connected cities often experience large and early outbreaks, while rural regions follow after some delay. This hierarchical structure of disease spread is influenced primarily by the multiscale structure of human mobility. However, during the COVID-19 epidemic, public health responses typically did not take into consideration the explicit spatial structure of human mobility when designing nonpharmaceutical interventions (NPIs). NPIs were applied primarily at national or regional scales. Here, we use weekly anonymized and aggregated human mobility data and spatially highly resolved data on COVID-19 cases at the municipality level in Mexico to investigate how behavioral changes in response to the pandemic have altered the spatial scales of transmission and interventions during its first wave (March-June 2020). We find that the epidemic dynamics in Mexico were initially driven by exports of COVID-19 cases from Mexico State and Mexico City, where early outbreaks occurred. The mobility network shifted after the implementation of interventions in late March 2020, and the mobility network communities became more disjointed while epidemics in these communities became increasingly synchronized. Our results provide dynamic insights into how to use network science and epidemiological modeling to inform the spatial scale at which interventions are most impactful in mitigating the spread of COVID-19 and infectious diseases in general.

Design, develop, and implement the strategic information system on health, dependence, and healthy aging: an analysis of the Mexican experience.

BACKGROUND: The Decade of Healthy Aging (2021-2030) emerges as a 10 years strategy to improve the lives of older adults, their families, and the communities in which they live. One of the actions defined in this framework is related to improving the measurement, monitoring, and understanding of characteristics, factors, and needs related to aging and health. The aim was to analyze and assess the process of construction and development of the Strategic Information System on Health, Funcional Dependence and Aging (SIESDE, for its acronym in Spanish). SIESDE will provide strategic information in Mexico at the municipal, state, and national levels that support the public policies on healthy aging. METHODS: The system processes and analyzes the data sources of the Health Information Systems and the National System of Statistical and Geographical Information. SIESDE comprises three components: (1) Design, construction, and evaluation of the indicators; (2) storage, management, and visualization, and (3) diffusion and translation of information. RESULTS: A total of 135 indicators were built on seven themes: (1) demographic, socioeconomic, and aging conditions, (2) health, (3) functional dependence, (4) healthy aging, (5) health services, (6) social and physical environments, and (7) complex indicators. CONCLUSIONS: SIESDE is an effective system for providing an overall view of health, aging, and functional dependence.

An Integrated Approach: A Hybrid Machine Learning Model for the Classification of Unscheduled Stoppages in a Mining Crushing Line Employing Principal Component Analysis and Artificial Neural Networks.

This article implements a hybrid Machine Learning (ML) model to classify stoppage events in a copper-crushing equipment, more specifically, a conveyor belt. The model combines Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) with Principal Component Analysis (PCA) to identify the type of stoppage event when they occur in an industrial sector that is significant for the Chilean economy. This research addresses the critical need to optimise maintenance management in the mining industry, highlighting the technological relevance and motivation for using advanced ML techniques. This study focusses on combining and implementing three ML models trained with historical data composed of information from various sensors, real and virtual, as well from maintenance reports that report operational conditions and equipment failure characteristics. The main objective of this study is to improve the efficiency when identifying the nature of a stoppage serving as a basis for the subsequent development of a reliable failure prediction system. The results indicate that this approach significantly increases information reliability, addressing the persistent challenges in data management within the maintenance area. With a classification accuracy of 96.2% and a recall of 96.3%, the model validates and automates the classification of stoppage events, significantly reducing dependency on interdepartmental interactions. This advancement eliminates the need for reliance on external databases, which have previously been prone to errors, missing critical data, or containing outdated information. By implementing this methodology, a robust and reliable foundation is established for developing a failure prediction model, fostering both efficiency and reliability in the maintenance process. The application of ML in this context produces demonstrably positive outcomes in the classification of stoppage events, underscoring its significant impact on industry operations.

Capability of big data to capture threatened vertebrate diversity in protected areas.

Protected areas (PAs) are an essential tool for conservation amid the global biodiversity crisis. Optimizing PAs to represent species at risk of extinction is crucial. Vertebrate representation in PAs is assessed using species distribution databases from the International Union for Conservation of Nature (IUCN) and the Global Biodiversity Information Facility (GBIF). Evaluating and addressing discrepancies and biases in these data sources are vital for effective conservation strategies. Our objective was to gain insights into the potential constraints (e.g., differences and biases) of these global repositories to objectively depict the diversity of threatened vertebrates in the global system of PAs. We assessed differences in species richness (SR) of threatened vertebrates as reported by IUCN and GBIF in PAs globally and then compared how biased this information was with reports from independent sources for a subset of PAs. Both databases showed substantial differences in SR in PAs (t = -62.35, p ≤ 0.001), but differences varied among regions and vertebrate groups. When these results were compared with data from independent assessments, IUCN overestimated SR by 575% on average and GBIF underestimated SR by 63% on average, again with variable results among regions and groups. Our results indicate the need to improve analyses of the representativeness of threatened vertebrates in PAs such that robust and unbiased assessments of PA effectiveness can be conducted. The scientific community and decision makers should consider these regional and taxonomic disparities when using IUCN and GBIF distributional data sources in PA assessment. Overall, supplementing information in these databases could lead to more robust and reliable analyses. Additional efforts to acquire more comprehensive and unbiased data on species distributions to support conservation decisions are clearly needed.

Capacidad de los macrodatos para capturar la diversidad de vertebrados amenazados en las áreas protegidas Resumen Las áreas protegidas (AP) son una herramienta esencial para la conservación en medio de la crisis mundial de biodiversidad. Es crucial optimizar las AP para que representen a las especies en peligro de extinción. La representación de vertebrados en las AP se evalúa con las bases de datos de distribución de especies de la Unión Internacional para la Conservación de la Naturaleza (UICN) y del Sistema Global de Información sobre Biodiversidad (GBIF). Es muy importante evaluar y abordar las discrepancias y sesgos en estas fuentes de datos para tener estrategias de conservación eficaces. Nuestro objetivo es conocer las limitaciones potenciales (por ejemplo, diferencias y sesgos) de estos repositorios globales para representar objetivamente la diversidad de vertebrados amenazados en el sistema global de AP. Analizamos las diferencias en la riqueza de especies (RE) de vertebrados amenazados según los informes de la UICN y GBIF en AP a nivel mundial y luego comparamos el grado de sesgo de esta información con los informes de fuentes independientes para un subconjunto de AP. Ambas bases de datos mostraron diferencias sustanciales en la RE en las AP (t = ­62.35, p = <0.001), pero las diferencias variaron entre regiones y grupos de vertebrados. Cuando comparamos estos resultados con datos de evaluaciones independientes, la UICN sobreestimó la RE en un 575% en promedio y el GBIF la subestimó en un 63% en promedio, de nuevo con resultados variables entre regiones y grupos. Nuestros resultados indican la necesidad de mejorar los análisis de representación de los vertebrados amenazados en las AP para que se puedan llevar a cabo evaluaciones sólidas e imparciales de la efectividad de las AP. La comunidad científica y los responsables de la toma de decisiones deberían tener en cuenta estas disparidades regionales y taxonómicas al utilizar las fuentes de datos distribucionales de la UICN y del GBIF en la evaluación de AP. En general, complementar la información de estas bases de datos podría conducir a análisis más sólidos y fiables. Está claro que se necesitan esfuerzos adicionales para adquirir datos más completos e imparciales sobre la distribución de las especies para apoyar las decisiones de conservación.

Correlation between disease severity indices and quality of life measurement tools in atopic dermatitis patients / Correlación entre los índices de gravedad de la enfermedad y las herramientas de medición de la calidad de vida en pacientes con dermatitis atópica

Abstract Introduction. Reports regarding the correlation and effect size of change of the full spectrum of quality of life and disease severity measures applied in-person to patients with atopic dermatitis are scarce. Objectives. To assess quality-of-life with 3 different instruments and to evaluate disease severity indices and to determine their correlation and effect size of change between two measurements. Materials and methods. Patient-level data were obtained through two in-person visits. Sociodemographic information and data related to disease distribution, severity (through the BSA, EASI, SCORAD, POEM, and itching scales), and the impact of atopic dermatitis on quality of life using the DLQI and Skindex-29, and EQ-5D, were assessed. The correlation between change in quality-of-life scores and disease severity scores in addition to the standardized effect size were also evaluated. Results. Only 139 out of 212 patients completed the follow-up visit. BSA highly correlated with SCORAD and EASI, and the lowest correlation was found with POEM. The best correlation of pruritus VAS was found with sleep disturbance. The SCORAD score highly correlated with EASI, and the lowest correlation was found with POEM. The magnitude of the effect at initiation of the study vs follow-up was in average moderate to important. Conclusions. Patients with atopic dermatitis experience a substantial burden on quality of life. Disease activity correlates better with quality-of-life measurements when the disease is less severe after starting therapy. POEM and Skindex-29 seem to be optimal to determine disease severity and quality of life in adults with atopic dermatitis.

Resumen Introducción. La información publicada sobre la correlación entre la magnitud del efecto de todo el espectro de la calidad de vida y la gravedad de la enfermedad en pacientes con dermatitis atópica es escasa. Objetivos. Evaluar la calidad de vida con tres instrumentos diferentes y los índices de gravedad de la enfermedad en pacientes con dermatitis atópica para determinar su correlación y el tamaño del efecto del cambio. Materiales y métodos. Los datos de los pacientes se obtuvieron a partir de dos visitas. Se evaluó la información sociodemográfica y los datos relacionados con la distribución y la gravedad de la enfermedad (mediante de las escalas BSA, EASI, SCORAD, POEM, prurito) y el impacto de la dermatitis atópica en la calidad de vida utilizando el Dermatology Life Quality Index, Skindex-29 y EQ-5D. También se evaluó la correlación entre el cambio en las puntuaciones de calidad de vida y las de gravedad de la enfermedad, además del tamaño del efecto estandarizado. Resultados. Solo 139 de los 212 pacientes completaron la visita de seguimiento. El área de superficie corporal se correlacionó fuertemente con el SCORAD y el EASI, y la correlación más débil fue con el POEM. La mejor correlación del prurito medido con la escala visual análoga se halló con la alteración del sueño. El puntaje SCORAD se correlacionó altamente con el EASI mientras que la correlación más baja se encontró con el POEM. La magnitud del efecto al inicio del estudio respecto al seguimiento fue en promedio de moderada a importante. Conclusiones. Los pacientes con dermatitis atópica experimentan una carga sustancial en la calidad de vida. La actividad de la enfermedad se correlaciona mejor con las mediciones de calidad de vida cuando esta es menos grave, después de comenzar la terapia. Los índices POEM y Skindex-29 parecen ser óptimos para determinar la gravedad de la enfermedad y la calidad de vida en adultos con dermatitis atópica.